Research And Application Of The Power Behavior Analysis Based On Big Data Processing Technology

With the introduction of the concept of big data,big data has quickly become a hot spot for scholars at home and abroad.Big data technology is also widely used in various industries.The power industry is one of the important areas for the application of big data technology.In recent years,with the pilot construction of smart communities,a large number of residential electricity consumption data has been accumulated.High frequency,mass,dispersion,etc.are important characteristics of users’ electricity consumption data.Not only that,there is a certain similarity and correlation between data.The massive electricity consumption data hides the electricity usage habits of electricity users,and uses data.The mining algorithm mines and analyzes the electricity consumption data,which helps the grid to personalize the users,thus providing better services and providing data support for the future development of power demand side response policies.This paper focuses on big data processing technology and power behavior analysis.Firstly,the related technologies of big data processing are researched and analyzed.The definition,characteristics and computational characteristics of big data are studied.The related technologies for processing big data,such as Hadoop platform,Spark distributed computing framework,Hive and HBase,are studied.database.Then the basic idea of K-means algorithm in clustering algorithm is analyzed.Aiming at the instability of the initial clustering center in K-means algorithm,a density-based maximum weight method is proposed.The UCI data set was used to carry out comparative experiments,which verified the accuracy and stability of the improved algorithm clustering results.In addition,in order to make the improved K-means algorithm can be used in big data scenarios,the improved K-means algorithm based on Spark is designed,and the correctness of the improved algorithm is verified by experiments.Then the improved algorithm is applied to the user.In the behavior analysis,through analyzing the CER dataset from Ireland,the load characteristics of various users are analyzed,and the specific power optimization schemes of various users are given.Finally,based on the big data processing technology,this paper designs and implements the electricity behavior analysis system based on Spark platform.The system realizes the functions of subdividing power users,providing power optimization suggestions,and managing power consumption data.The system better realizes the information construction project that applies big data processing technology to the power industry.